Full Transcript:

Steve: Good evening. It’s a great way to end a great day. Like to welcome to our evening keynote. Before Ray Kurzweil came along, computers were boring to most, they crunch data, they were big expensive lurking machines that were just beginning to enter the home and computers aren’t boring anymore. And Ray had a lot to do with it. He taught computers to read, to talk, to listen and to make music. His devices were expensive at first, but he saw the day when you’d be able to go to your local toy store and buy a computer or scanner or a musical keyboard or a speak and spell child’s game. At the time, he was one of the few who saw already of that and help make it happen. Histories inspiring on many grounds up, one of my journalism school classmates blinded in a hunting accident when he was seven, Ray has proof, living proof that the day of the iconoclastic multi-disciplinary inventor did not die with Thomas Edison. In fact, Inc Magazine ranked him number eight among entrepreneurs in the United States, calling him the rightful heir to Thomas Edison. PBS included Ray as one of the 16 revolutionaries who made America along with other inventors of the past two centuries, one of the top 16 in two centuries. As one of the leading inventors of our time, Ray really did do all those things to the computer. He was the principal developer of the first CCD Flat Bed scanner, the first OmniFont optical character recognition, the first print to speech reading machine for the blind, the first text to speech synthesizer, the first music synthesizer capable of recreating the grand piano an other orchestral instruments and the first commercially marketed large vocabulary speech recognition software.

His website, KurzweilAI.net has over one million readers. Among his many honors, he is recipient of the $500,000 MIT Lemelson prize, the world’s largest prize for innovation. In 1999, he received the National Medal of Technology, the nation’s highest honor in technology from President Clinton in a White House ceremony. In 2002, he was inducted -- you know you’re around the White House, you never know, Ah, -- inducted it to the National Inventors Hall of Fame established by the US Patent Office. Ray Kurzweil has received 13 honorary doctorates and honors from three US Presidents. He’s written five books, four of which have been national best sellers. His Age of Spiritual Machines has been translated into nine languages, and was the number one best selling book on Amazon in science. His latest book, The Singularity Is Near, was in New York Times’ best seller and had been the number one book on Amazon in both science and philosophy. He is here today to talk about the accelerating future of information and for students and parents here, his story I think is especially inspiring. Unless at least some of us follow in Ray’s footsteps, creating things that never existed rather than following a safe career path incremental change that sort of thing. Our economy won’t be safe at all. We have to continue innovating, not just incrementally, or we lose our economic leadership, our technology leadership to other countries. Others can make things cheaper, they may even make things look better, innovation is our only edge. Ray is still making news. The current issue of Fortune magazine, the one that you’re going to get in a couple of days, has a six page article on him. You’re getting the preview. I’d like to ask you to help me welcome Ray Kurzweil.

Ray Kurzweil: Well, thanks Steve for that warm introduction and I’ve been looking forward to this conference. Killer Apps has always been close to my heart being an inventor decided I would be an inventor when I was five, lately I’ve gotten involved with some medical technologies and I’m not sure we want to call those killer apps but we’ll find some different phrase and broadband is going to be increasingly influential as we engage in virtual reality environments and spend more and more of our time in virtual reality and like just this morning, I needed to give a speech in Ontario, I happen to be here in Fort Wayne so I actually appeared there using a technology called teleportex, it’s not video conferencing, it’s 3-dimensional, full emergent virtual reality and appeared as if I was there, life size, real time, I could see the audience, they could see me as I moved around, they saw the local background behind me, so it looked like I was actually there, I am actually the only speaker in the world that has his own system like this and I give because it’s scheduling issues and I get a lot of invitations from Asia, Europe, I use this technology quite a bit, so that’s virtual reality today, it’s a bit cumbersome, we have to send a technician with the equipments to the venue and this fairly elaborate setup. This will be ubiquitous technology using broadband thus we go into the future will have images written directly to our retina from our eyeglasses that’ll solve the problem of wanting big displays while having devices that are tiny, we’ll have these tiny devices that are eyeglasses will create virtual displays that are high definition, hovering in air or can take over your whole visual field of view and put you in a virtual reality environment, you should go there by yourself over the other people and share information like we’re doing now, like I did this morning, virtually, but this will be something we can all do as easily as making a cellphone call. In fact the telephone was a first virtual reality technology and that was the first communication link that was not broadband but that did foster our ability to communicate with each other, something that only our species does and since I’ve decided to be an inventor at age five as I mentioned, I’ve been an ardent student of technology trends because I realized pretty early on that the key to being successful as an inventor was timing, and most technologies, most inventors failed not because they can’t get the thing to work, but because the timing is wrong, not only enabling factors around placement they need to be. So I began building these models of technology trends and tracking how technology evolves and being an engineer, I collected lot of data and I found that these models were actually quite predictive and this is taken a life of its own, I have a group of 10 people now that gathers data in many different fields and we build mathematical models and -- we’re able to predict how technology will evolve decades in the future and you might say “Well, how could that be?” Because a common wisdom is you can’t predict the future. And that’s true for specific projects, if you ask me “How’ll this killer app do?” Or “What’ll the next wireless standard be will it be CDMA G3 -- generation three, generation four?” That’s hard to predict.

Will Google stock be high or low than it is today three years from now, that’s hard to predict, but if you ask me what will the cost of a Mips of computing be in 2010, or the special resolution of brain scanning in 2012, or the cost of sequencing a base pair of DNA in 2014, I can give you a figure and it’s likely to be accurate then I say this now, not just over fitting to pass data, but making these forward looking predictions for several decades for example, I saw the Darpen net doubling every year in the 80s, went from $10,000 to 20,000, one year that’s $40,000. Will doubling every year, is this exponential growth as multiplying by a 1,000 in 10 years, a billion in 30 years, so I figured that in the 1990s, there should be $20 million is going to 40 million to 80 million to 160 million and would be a world wide communication that so I described something like the world wide web, not by that name, emerging in the mid 1990s that was resoundly criticized in the 80s when only a couple of 1,000 scientists were using this very unreliable and very low bandwidth Darpen net but it came out right on schedule, the first reference of the world wide web in New York Times was late 1993, and so the Chess supercomputers doubling in power every year that added 40 points every year to the Chess score of these computers because the Chess score is a logarithmic scale so as they got exponentially better, it added 40 points that put across over in 1998, so I predicted a computer will take the World Chess Championship in 1998 in mid 80s that seemed absurd when the average Chess player could beat the best Chess machines, and then in 93, Kasparov, the Chess champion was asked about my prediction and he said “That’s ridiculous. I’ve played the best Chess machines in the world and they’re pathetic, they’re predictable, they’re brittle, there’s no way they’ll ever touch me.” And he had that confidence based on what he saw and people mostly based their expectations on what they see and not really taking in the consideration this exponential growth, well, if it was a true observation in 93, they saw it passed them in 97. The Genome project, we now see that as a hallmark of science, one would assume that must have been a big announcement in 1991, they announced this 15 year project to sequence a human genome but that was dismissed by mainstream critics who said that in 1989 they had their best PCs students and most advanced equipment around the world, they manage to sequence 110 thousands of the genome, it’s no way they’re going to do this in 15 years. And halfway through the project, the skeptics were still going strong saying I told you this wasn’t going to work, I mean here you are halfway through a 15 year project and you finished 1% of the project, but if you double 1% seven more times, you get a 100%, that’s exactly what’s happened that’s continued passed the end of the Genome project four years ago and every other example of biology has been gearing up in this exponential fashion.

The price performance, the capacity the bandwidth of information technology right now is doubling every year. And even that rate has sped up, took it three years to double the price performance of computing in 1900, two years, the middle of the 20^th century, it was 12 months in the year 2000, it’s now about 11 months, or this is slow acceleration and the rate of acceleration, but just consider doubling every year that’s what’s applying by a billion in 30 years, you take the second level of exponential growth, it’s 25 years to be exact. We’re also shrinking technology in an exponential rate. According to my models, at rate of 100, but 3D volume for decade so in 25 years, that’s a 100,000. So imagine how influential information technology is today. How we use broadband and the computers and these tiny devices that fit in our pocket and how it really transformed the world and how the internet and search engines are greatly expanding our access to each other and to information and then imagine multiplying this by a billion fold over the next quarter century. Well, at the same time, we shrink the size of these devices by a factor of 100,000, the 3D volume and you will get some idea of what will be feasible. But to come back to my earlier point about how can you predict the future, the common wisdom is that you can’t, it’s true that you can not predict specific projects, but the overall impact is very predictable and you might wonder well, how could that be, or we see other examples in science are predictable results coming from a chaotic, dynamic, random system where each element is highly unpredictable and the quite essential example of that is thermodynamics which comes from the nineteenth century which predicts the properties of a gas and then actually models the gas as being made up of a large number of particles, each of which follows what’s called a random block, meaning it’s just follows completely unpredictable path, so you can tell where this molecule will be 10 seconds from now, but the overall gas, the overall system made up of a large number of unpredictable particles, is very predictable. According to the laws of thermodynamics to a very high degree of precision so if you have a large dynamic system, you can predict it’s overall outcome and technology evolution is just such a dynamic, chaotic system in which the overall results are highly predictable and I’m going to show you a few dozen examples, we’ve hundreds of these but if you can measure the information content, our process whether it’s speed of computers, or the monogenetic sequencing or that the scale of pro-dynamic simulations, many different examples, they follow these exquisitely exponential progressions that are highly predictable and the other observation is that this exponential growth is not just limited to electronics.

You’ve probably heard of Moore’s Law which is a shrinking of components on an integrated circuit, so you can put twice as many every two years on a chip and they run fast because they’re smaller, that’s given exponential growth to computing and to electronics, but it’s not just limited to that. It applies to everything in which we can measure the information content and an area that is now transforming from having been a pre information era to a becoming an information technology is health and medicine, which I mentioned earlier that didn’t used to be an information technology or an information science. It was basically hit or miss, we’d find something, oh here’s something that lowers blood pressure, we don’t know why this works but it seems to have some benefit but also has lots of side effects and most of the drugs on the market today were done that way, process called drug discovery and that process was automated to some extent so that they could automatically try out 50,000 compounds and try to find something that combats a specific pathogen or lowers blood pressure, but we didn’t have the tools to really reprogram biology, in fact we didn’t understand biology as a set of information processes but biology is essentially a set of information processes. It starts with our genes, those are linear sequences of data. We have these 23,000 software programs inside us called genes which haven’t changed much in thousands of years and they involve conditions were quite different. For example, the fat insulin receptor gene which evolved a long time ago basically says hold on to every calorie because in next hunting season may not work out so well and that was a good strategy a thousand years ago when calories were few and far between. If you have it and bound some calories, you wanted to store them in your body, there were no refrigerators. In fact the fat insulin receptor gene was the innovation that allowed animals to roam around plains don’t have a fat insulin receptor gene. Well, this now underlies an epidemic of obesity, it’s not a good strategy in the era of abundance to store every calorie when you’ve got more than enough already stored. Or what happened if we turn that gene off in the fat cells this was tried at Towson Diabetes Center and we have a new technology, RNA interference that can turn genes off but these animals eat ravenously and remain slim and it wasn’t a fake slim this has got the health benefits of being slim, they didn’t get diabetes, they didn’t get heart disease, they live 20% longer, they got the benefits of caloric restriction, all doing the opposite and there’re five pharmaceutical companies rushing to bring fat insulin receptor gene inhibitors to the human market. This is one of the 23,000 genes we’d like to consider either turning off or modifying their new form of gene therapy where we can modify genes or actually add new genes.

I’m involved with one company where we take a cell out of the lungs, modify it in vitro adding a new gene and then we can inspect that it got done correctly, then we multiply it a million fold which is a well established technology injected back into the body these millions of modified cells, they go through the blood stream, they are lung cells so they end up in the lungs and this is cured a fatal disease pulmonary hypertension in animals and this is now being tested in humans and the initial results are quite positive. This is one example of many of being able to really reprogram biology, so we will have not just designer babies but designer baby boomers which is something I’m personally more interested in. But, the point is that biology and therefore health and medicine is becoming an information technology and as such it is now subject to just what I call law of accelerating new trends. This doubling of the price performance and capacity of these information technologies in every arena and the I’ll describe little bit later how even energy which is very much not an Information Technology today based on an old industrial technology of fossil fuels will actually transform using nanotechnology within 20 years to begin Information Technology and there will be subject to this law of accelerating returns. Now, these models of predicting technology trends are developed initially to time my own technology projects and that’s still the primary application although a fall out is that we can then anticipate what these technologies will be like, what’ll broadband be like in 10 years or 20 years, computers devices or health and biological technologies, we can anticipate what their capacity will be and we can’t build inventions with computers circuit 22 or 25 but we can talk about them and we can invent at least your books and through discussions that the products and technologies and the killer apps of 10, 15, 20 years from now. So, I spend a little bit of time doing that but to show you one example, it was mentioned that I’ve been involved with reading machines for the blind for 30 years, developed the first batch of featuring machine for the blind in 1976, it was a little bit smaller than this lectern, quite expensive and they’re up with some libraries, Steve, you wanted it buy one and over the -- I’ve stayed involved in this field and over the years they’ve gotten smaller and smaller and actually more and more powerful and keeping with rest of electronics but up until recently, it was still a device that was on your desk and blind person will bring reading material back to their desk and read it.

Well, if you think about your day today, how much reading material and just incidental reading you did as you go through the day, it’s really part of being -- taking part in the visual world, science on the wall, bank ATM display, menu at a restaurant, you’d like to be able to read as you go through the day, so in various presentations at disability technology conferences, I would say will some day a blind person will be able to take a device out of their pocket and just read it all the materials they go through the day. So, four years ago, actually five years ago now, 2002, I had a conversation with Dr Marc Maurer, the President of the National Federation of the Blind, and I’d worked with that organization on the first reading machine and he said “Ray, you’ve been talking about this pocket size reading machine for years, when this is going to be possible?” And I said “Well, according to our models of electronic technology, digital cameras and pocket computers, the requisite hardwares of all these application will be available in four years, 2006. Second quarter to be exact.” And he said “OK, how long will it take to develop the software?” And I said “Well, we can’t just take OCR and speech synthesis and compress them into the PDA. We’ve to add a new layer of software because there’s a blind person holding this device as three different degrees of freedom of rotation and tales, images will be curved, there be uneven illumination from the real world, you don’t want control illumination of scanner, pro quality optics, distorted images…” I listed seven or eight vagaries of real world print taken by a handheld camera. He said “OK, I understand, how long will it take.” I said “Four years.” He said “OK. Let’s get started.” So we got started in 2002 and right on schedule, this spring of 2006, the requisite digital cameras with PDA technology became available, a little bit to my surprise, we actually the software project done on time and in last summer, we introduced the KurzWeil National Federation of the Blind Reader which is this device here and there’s now a thousand blind guys and girls going around, reading the labels on their clothing, remainders at the book store handouts to meetings like this and really reading as they go through the day and I’d give you a little demonstration of this.

Machine Recording: This system is in shooting mode. Camera is off, I’m ready.

Ray Kurzweil: You can see synthetic speech has improved.

Machine Recording: Camera is on. Field of view report. Top and left edges are visible 59% filled, taking picture.

Ray Kurzweil: The field of view report is actually quite comprehensive little. For blind person just pointing at a wall, it’ll actually tell him or her to move to the left.

Machine Recording: Free processing picture.

Ray Kurzweil: Like getting off the left side of a poster.

Machine Recording: Camera is zero degrees clockwise relative to the page.

Ray Kurzweil: I think I hit that on, that’ll actually rotate.

Machine Recording: Page one. GN 189. The AI winter is long since up and we’re well into the spring of neuro AI. Most of the examples about the research project just hand to 15 years ago, if all the AI systems in the world suddenly stopped functioning, our economic infrastructure would grind to a halt, your bank would cease doing business, most transportation would be settled, most communications would fail. This was not a case the decade ago, of course, our AI systems are not smart enough to get organized start you a conspiracy strong AI. If you understand something in only one way, then you don’t really understand it at all. This is because if something goes wrong, you get stuck with the thought that just sits in your mind with nowhere to go. Speaking cancelled. Camera is off. And unsave doc. Good bye.

Ray Kurzweil: That is a passage from my book. It’s talking about artificial intelligence. People often ask me whatever happen, AI anyway reminds me people that going to the rain forest and say “Well, where is the species that was supposed to be here.” When these 50 species advanced within 25 feet of them, but they are invisible. They’re deeply integrated into the ecostructure. AI is deeply integrated into our economic infrastructure and there’re hundreds of examples. Every time you send an email, Intelligent Algorithms route the information. Same for cellphone calls, Intelligent Algorithms fly and land the air planes, guide intelligent weapon systems, make billions of dollars a day of financial decisions to automatically detect credit card fraud, help design products where computer system design, control just in time, inventory levels help build products and robotic, factories automatically diagnose electrocardiogram, same for blood cell images, and I can list a hundred other applications and as the passage points out, if all the AI, Artificial Intelligence programs, programs that are performing functions that used to require human intelligence, were to stop tomorrow, our modern infrastructure will grind to a halt and that wasn’t true 25 years ago. 25 years ago or even 20 years ago, these were research projects. So -- and the narrowness of these AI applications is gradually getting less narrow. So, we’ll talk more about that, but let me show you quickly some examples of just how pervasive this exponential growth is, of Information Technologies. Because of the exponential growth of Information Technology, the paradigm shift rate, basically the rate of technical progress is itself accelerating. Now you might say “Well, that’s obvious”, but it’s not something that people intuitively consider. When I was at a conference a few years ago on the 50^th anniversary of the discovery of the structure of DNA, all of us speakers were asked to take, we made progress in last 50 years and medicine, what’d the in next 50 years bring? All the speakers there, except for one other guy, Bill Joy, and myself use the last 50 years as a model for the next 50 years but that’s wrong. I’m quoting on all of us to make 32 times as much progress in the next 50 years as this last 50 years. So even Jim Watson himself, the co-discoverer of DNA, said “Now in 50 years, we’ll have drugs and then eat as much as you want and remain slim.”

And I said “We’ve done that in animals. There’re five pharmaceutical companies rushing to bring patents on receptive gene inhibitors using RNA interference to the human market. It’ll be well within one decade, not five.” All of their predictions were generally overly conservative by failing to take this exponential growth into consideration. So, these graphs are what I call logarithmic graphs as you go up the graph, it’s multiplying something by powers of 10, so each level, above the level, below it is 10 times greater and a straight line or logarithmic graph is exponential growth. So, the telephone, I mentioned that was the first virtual reality technology that took half a century to be adopted by a quarter of the US population. Cellphone did that in seven years. These early communication technologies telephone, television, radio took decades to be adopted by a mass audience, and this the cellphone, the web, personal computer were adopted in just a few years time. In this acceleration has continued. Think back five or six years ago, most people didn’t use search engines, and we think of life without search engines, that sounds like ancient history. That was five years ago. Social networks, blogs, podcasts, I mean these terms didn’t exist three years ago. The pace of progress has continued to accelerate. And I’ve all theories as to why this is the case. It’s really a theory of evolution, both biological evolution and technological evolution and basically, an evolutionary process evolves a capability, adopts that capability and uses it to evolve the next stage, so the next stage goes more quickly and the fruits of the next stage grow exponentially. So this is double logarithmic graph on the x-axis, it’s how long ago this paradigm shift took place. On the y-axis, it’s how long it took for that paradigm shift to be adopted this is all in powers of 10.

So the first paradigm shift in evolution, basically the evolution of DNA, actually RNA came first. That took a billion years but then evolution adopted DNA, has used it ever since. And the next stage when a hundred times more quickly, the Cambrian explosion when all the body plans of the animals evolved, that only took 10 million years and then that became a mature technology and so evolution concentrated on something else, higher cognitive function, that only took a few million years and then evolution evolved the technology creating species that took only a few hundred thousand years. It’s actually only three simple genetic changes that distinguish us from our primate ancestor and these changes comprise only a few tens of thousands of bytes of information but they were very significant, they were the enabling factors for technology. One is a larger skull so we can have a bigger brain at the expense of a weaker jaw, so don’t get into a biting contest with another primate. More of the brain is devoted to the shrivel cortex where we can do abstract reasoning, we can do variety of experiments in our mind, what if I took that stone and that stick and tie them together with that twine, that could create a tool and extend my leverage and then we have an opposable appendage that allows us to actually manipulate the environment and carry out these variety of experiments and create tools. They might think that a chimpanzee’s hand looks very similar. It looks similar but the pivot point is done one inches, just a bad design, evolution hadn’t finished. If you watch a chimp, they’re pretty clumsy, they don’t have a power grip, they don’t have fine motor coordination, they can’t really build tools and there’s discussion about chimps using tools but it’s not technology, the tools don’t evolve, they don’t the tools to create out the tools. Tools never change, their basic can find a stick and grab it, hold it pretty clumsily and stick it into a whole but that’s about it, we can actually create tools and then use the tools to create other tools and so technology, is this whole evolutionary process they respond from the technology creating species. And the first step and that were little bit faster.

Tens of thousands of years for the first steps in technology, stone tools, fire, the wheel and then, it kept accelerating because we used tools to create new tools. 50 years ago, the first computers were designed pen on paper, wide with screwdrivers, to gears, to build. Now, a computer designer will use a computer and 12^th generation computer system design software to automatically compute 14 layers of intermediate design and a new computer can be designed in a matter of days and this forms a straight line on this double logarithmic graph showing the continual acceleration of biological evolution and technological evolution leading smoothly from biological evolution. And some people looked to this and said, “Well, Kurzweil only put points on the graph if they fit on the straight line.” And if there was a paradigm shift that didn’t fit on the straight line I just didn’t bother.” That included, so to address that criticism, I took 15 different lists from 15 different thinkers, called Sagan’s Cosmic Calendar, Encyclopedia Britannica, American Museum of Natural History, Dozen Dollar list as to what they thought the key events were in biological and technological evolution and you can see there’s some disagreement. Some people include that Darpanet with the internet and so it is 25 years, not 10 years, some people think the Cambrian explosion took 25 million years, not 10 years million years, this disagreement when human language started, buts you can see there’s definitely a clear trend line, a great clear acceleration, even though there’s a slight spreading of the points. Nobody thinks the internet took a million years, nobody thinks the Cambrian explosion happened in ten years. Not much happened in a million years, a billion years ago, there’s a very clear acceleration in this evolutionary process. And as I mentioned, the power of Information Technology is doubling every year and it really applies to every type of Information Technology. So, a personal experience, when I came to MIT, they had a computer shared by thousands of us, it took up about the size of these twos audience sections here and it had 144,000 bytes of memory, a quarter of a Mip, thousands of times less powerful than the computer in your cellphone today.

Now, people say -- another criticism of my projections is Kurzweil takes these exponentials and just projects them in the feature and we all know that exponential growth can’t go on for ever. Rabbits on Australia, they grow exponentially, but then that exponential growth hits a wall when they eat up all the foliage and they can’t expand any more. Well, that happens to be true for specific paradigms, but what happens in Information Technology is when one paradigm that is bringing exponential growth to electronics and computer technology and communications hits a wall, it creates research pressure to create the next paradigm and the next paradigm picks up with the last one left off. In Moore’s Law which you’ve probably heard of, was not the first to bring exponential growth to computing, it was the fifth paradigm, here I put 49 famous computers on a logarithmic graph, this goes back over a century to the first data processing equipment that is used in the 1890 census that used these all punch card machines which was subsequently shipped to the Florida Election Commission. Interesting that that joke still works, very hard to let down a reputation, even though they did well in the last election. The next tripe was a whole new different paradigm realize Alan Turing cracked the German Enigma code with a relay based computer and as a lot of interesting war time literature about how Churchill and Roosevelt couldn’t quite use the information that easily without tipping of the enemy that their code had been cracked, so they would try to convince the enemy they got the information some other way, if they knew a convoy of ships was coming, they’d send over long flier, the German sailors would say “Oh, we’ve been spotted.”

That was just a ruse so they didn’t think that the code had been cracked, but then in the battle of Britain, they three to one outnumbered Royal Air Force, won that battle providing a launching pad for a D-day invasion, so that was relay based computers. In 1950’s, the third paradigm, vacuum tubes came in and the computers were build with vacuum tubes, CBS predicted the election of Eisenhower, first time the networks did that, and then they were shrinking vacuum tubes, every year making them smaller and smaller to keep this exponential growth of computing going and that then hit a wall, they couldn’t shrink the vacuum tubes anymore and keep the vacuum and that was the end of the shrinking of vacuum tubes, it was not the end of the exponential growth of computing, we went to the fourth paradigm, transistors which are not small tubes, whole different approach and then we’ve had several decades of Moore’s Law, shrinking components on the integrated circuits and there’s been regular predictions that that will come to an end, the first predictions were 2002. Intel now says 2022, by 2020, the key features on an integrated circuit will be 4 nanometers that’s the width of 20 carbon atoms and around that, we won’t be able to shrink them anymore that’ll be the end of Moore’s Law, but it won’t be the end of the exponential growth of computing. We’ll go on to the sixth paradigm which is the three dimensional molecular commuting. Chips are already quite dense but they’re flat, they’re two dimensional, we live in a three dimensional world, our brain is organized in three dimensions, we mostly use the third dimension and this was a controversial notion when my 1999 book, Age of Spiritual Machines came out, there’s been so much progress in this field over the last eight years including getting these self organizing, three dimensional molecular circuits to work, including my favorite, Nanotubes that this is very much a mainstream expectation now.

Intel has these circuits working, there’s actually a Nanotube based memory due to hit the market next year and they expect the crossover point to be in the teen years and but notice how smooth this progression is. I mean this is the results of millions of people innovation and all kinds of vagaries of human history, went through two world wars, a cold war, the great depression and a lot of other things that happened in the last 120 years and you have this very smooth progression and it’s not a straight line as you can see is that’s the slow second level of exponential growth and super computers marching along exponentially. I predicted in my last book, The Singularity Is Near, which came out a year and a half ago that super computers would hit 10¹⁶, that is 10 million billion calculations per second by 2013, that’s a significant threshold because that’s the most conservative estimate of the amount of computation needed to simulate the human brain and generally my predictions are considered radical when they come out, they end up by design being slightly conservative. Just recently, IBM and Japan announced super computer projects they hit that threshold by 2010 and I don’t want to devolve in these examples of electronics. You’re probably familiar with them, but look at this graph here, this is the cost of a transistor, so when I was a high school student growing up in New York, I would hang out at the Surplus Electronic shops in Canal Street and buy something about four times the size of this for $50, equivalent to one transistor but a lot slower. Come 1968, I could buy a whole transistor, a lot faster than the relay for just $1. 2002, you could buy 10 million transistors for a dollar. Today, it’s hundreds of millions of transistor for a dollar. Now, you’ve heard these fantastic comparisons of how far we’ve come in terms of electronics, although it continues to be impressive to consider these many examples, keep in mind that that also applies to a comparison of today to the future.

We’ll make another billion fold increase over the next 25 years, but the other interesting thing about this graph is, look at how smooth this progression is. This it looks like I’ve put up some table top experiment but this actually the measure of the innovation and the killer apps of millions of people in thousands of companies in dozens of countries, all competing with each other and there’s been wars and bankruptcies and IPOs and out of all this chaotic human behavior in history, you would think that this would be a very erratic curve. Look at how smooth and predictable this is and as we made those transistors cheaper, they’re better because they’re smaller so the electrons have less distance to travel so they’re faster, we’ve had smooth exponential growth in the speed. The cost of a transistor cycle has come down by half about every year and that’s 50% deflation in electronics, turns out that every other example that we can point to, of Information Technology, where we can measure the cost, has a 50% deflation rate. The cost of genetic sequencing has come down by half every year, the cost of collecting brain data cuts come down by half every year, the cost of databases in many different fields comes down by half every year and also doubling the amount of human knowledge that is online, every year and depending on what week it is, the economists will worry about inflation or deflation and then they’ll tell you that deflation is bad also, we had massive deflation during the American depression and the concern is that as the more and more economy becomes comprised of Information Technology, it’s already quite substantial, it’s growing, it will be most of the economy by the 2020s, and if that has a 50% deflation rate, then its size in economy will shrink. Yes, we will buy more capability if we can get it for half the cost, but we’re not going to double our consumption year after year of Information Technology and ultimately, we’ll not just be electronics and information like music files and movies, it’ll also be physical stuff with nanotechnology which will be in Information Technology, we’ll be able to basically print out three dimensional objects that can perform a wide range of functions, for example a shirt or a meal a or a computer or a solar panel and basically physical stuff will also be in Information Technology, just as we can take an information file now and create a recorded album, a movie, a book, we’ll also be able to create these physical objects and if you can get them for half the cost each year, that’s going to lead to a shrinking in the economy as these of measuring constant currencies for various reasons, that’s not a good thing. That’s actually not what we see. We’ve actually more than doubled our consumption of Information Technology every year. In every area of Information Technology, there’s been 18% growth in constant dollars of the last half century, despite the fact it can get twice as much capability, each year for the same amount of money and the reason is there’s new applications as price performance reaches certain levels, whole new application explode on the landscape. People didn’t buy iPods for $10,000 which is what it would’ve cost 10 years ago and broadband applications, they’re just waiting new forms of full emergent virtual reality for the cost of transmitting a bit to come down which it does by half every year, so these applications will explode in the landscape as new price performance makes them possible and I mentioned the biotechnology revolution, smooth decline in the cost of sequencing DNA from $10 for a base for 1990, a fraction of a penny today, the first genome cost a billion dollars.

I met recently with the Directors of National Institute of Health and they’re collecting a million genomes to reliably match gene states with disease states. Well, they wouldn’t have done that when the genome cost a billion dollars, now they were close to a $1000 genome, billion dollars to collect a million genome is a reasonable investment. This is the amount of genetic data we’ve sequenced as slope on this log graph represents a doubling every year of the amount of slope on this log graph represents a doubling every year of the amount of genetic data we’ve sequenced, but look at how smooth this is. This again, it looks like it’s the I’ve put up a table top at sure, this is a measurement of thousands of companies all competing with each other, it’s not an organized process, and now we see this very smooth, very predictable exponential progression. The same thing is true of communications, broadband is already quite ubiquitous but broadband itself is quite variable, we’ll have ultra high broadband to really create full emersion, visual, auditory, virtual reality systems early in the next decade and it’s many different ways to measure communications, wired, wireless, fiber optic, number of bits moved around and so on, but no matter how you measured, there’s generally a doubling every 11 months, 12 months, 13 months depending on what you’re looking at. This is the graph I had in the 1980s of the internet then called the Darpanet, I had just a little piece of this but I saw the Darpanet doubling every year meant multiplying by 1000, 10 years predicted that this would be a world wide communication network in the mid 1990s. You look at the same data on a linear scale, it looks like this, this is the same data, but not on a log graph, on a linear graph. This is how we experience the world, we don’t live in a exponential domain, we experience it linear, it looks like the internet just came out of nowhere, the World Wide Web just exploded out of nowhere in the mid 1990s, but if you look at the exponential progression, you could see it coming. We’re shrinking technology at an exponential rate, a rate of 100 per 3-D volume per decade and we’re building systems at the molecular level, these are illustrations from Mary Crux’s book that introduced nanotechnology 20 years ago but we’re now actually building these kinds of systems and if I were to say that some day we’ll have blood cell size of ICs, nano-engineered with multi-nanometer features, going inside our blood stream performing therapeutic functions, you think “Oh, well, that’s pretty far out futuristic stuff.” Well, we’re doing it already, there’s already a first generation of blood cell sized devices with nano-engineered features that are performing therapeutic functions in animals. There’s four major conferences on this on BioMEMS, Biological Microelectronic Mechanical Systems, and dozens of very impressive experiments, one scientist cured Type 1 diabetes in rats with a blood cell sized device, seven nanometer pores, let’s insulin out in a controlled fashion, blocks antibodies because Type 1 diabetes is an odd immune disorder.

Scientists at MIT in the University of Rochester have a blood cell sized device that can actually detect the antigens specific to cancer cells, blood turned with the cell, burrow inside, release toxins and destroy the cell. There’s a lot of other impressive examples, this is a design for robotic red blood cell. Red blood cells are actually fairly simple, we understand how they work and it brings up an interesting observation about biology which is -- well, biology is very intricate, it’s also very sub optimal, once we actually learn its principles of operation, we can reengineer biological systems with nanotechnology to be thousand driven millions of times more capable. So a conservative analysis of these resperocytes robotic red blood cells indicates if you replace a portion of your red blood cells with these robotic versions, you could do an Olympic sprint for 15 minutes without taking a breath or sit at the bottom of your pool for four hours, so “Honey, I’m in the pool” take on a whole new significance. So, if we look at, say, the 21^st century, what this sick exponential progression of computation will continue, we’ll have plenty of computation at low cost to simulate systems as complex as the human brain, but what about the software? Or will these just be very fast calculators? The software is progressing on its own in terms of our artificial intelligence work. I mentioned that there’s already hundreds of examples of AI. you know economic infrastructure, but one very important source of how human intelligence works, is the human brain itself and it’s not hidden from us and we have this grand project, this 50,000 scientists and engineers who are figuring out how the brain works for one perspective or another and this is also scaling up exponentially the special resolution brain scanning is doubling every year, the amount of data we’re collecting on the brain is doubling every year, the cost of that data is coming down by half every year, but then another question is “Okay, we’re getting this information but can we understand it?” Dugg Hoffstead has said for years, “Well, may be our brain is just below that threshold necessary to understand our brain and if we were smarter and able to understand it, well, then our brain would have to be that much more complicated and we would never catch up with it.” And may be there’s a math theorem in there that our complex system can’t be so complex as to understand its own complexity.

It turns out that that’s not the case, as we’re getting data on specific regions, we’re finding that we can understand how they work, express the transformations they make the information in mathematical terms and simulate among the computers and test those simulations. This is a block diagram of a dozen regions of the auditory cortex which have been modeled and simulated and then sophisticated Psychoacoustic test applied to the simulation and they get very similar results as applying those same test to human auditory perception. The same thing is true for the cerebellum which is where we do our skill formation and that’s a very important region because that’s where comprising more than half the neurons in the brain and also for the visual system. There’s already a detailed simulation which performs very similar to human visual perception and this work is scaling up in exponential rate. That brings up another important question which is how complicated is the brain. Well, the brain is not simple but the apparent complexity is greater than the actual complexity of the design. Take the cerebellum, if I would give you a cerebellum, say, here, reverse engineer this, tell me how this works and you’ve looked at it and it was trillions of deeply interconnected connections. Any one of those trillions of connections was incredibly complicated and convoluted. You go all this, this, we’ll never figure this out well we have figured it out, it’s actually not that complicated there’s only a few genes that control it that actually comprise only a few tens of thousands of bytes of information.

Well, how can a few tens of thousands of bytes of information describe something that’s actually a billion times more complicated? Well, if you look at this image here which you may seen, it’s called the manual broad set, it’s a fractal, it looks like a very complex image and it’s on the cover of a book called complexities, considered a very complex image and it does look complicated and as you zoom in on it and blow up the image, there’s complexity within complexity without end. Well, so this is a very complicated image but design of the metal broad set it only six sliders long. Apply interactively it’s a fractal that actually describes the relationship with the human genome to the brain because what the genome says about the cerebellum is a four different types of neuron, they’re organized in one module of kind like this, now repeat that 10 billion times and add some random variation with each reputation and the secret of the design is it’s self organizing, so as a child learns to walk and to and to catch a fly ball, it gets filled up with meaningful information, but the design is actually only a few tens of thousands of bytes long and the whole design of the brain is about 30 million bytes. How do we know that? Well, it’s in the genome and the genome doesn’t have that much information in it, the whole genome is 800 million bytes including the so called junk DNA which isn’t junk but it strictly whether it is done sees that sequences that are repeated hundreds of thousands of times. ALU for examples is repeated 300,000 times and for those of you who are mathematicians, you know that if you have repetition like that, you compress information without losing anything, lossless compression, if you apply lossless compression to the genome, I talked about this is the book, you get down to about 30 to 50 million bytes and that describes the design of the human body and brain, but then it’s a needed of fractals that actually gets implemented. The point is not that brain is simple, the point is that it’s a level of complexity that we can’t deal with, that we are dealing with.

There’s already 20 regions that have been modeled and simulated there’s only several hundred altogether. I make the case in chapter 4 of my book that we’ll have the models and stimulations and really principles of operations of all several hundred regions within 20 years. All of this is driving economic growth. I’ve already mentioned this but we’ve had smooth exponential growth and productivity it’s gone from $30 to $130 in constant dollars of the value of an average hour of human labor and the adoption of these technologies is also an exponential. This is E-Commerce, smooth exponential growth, it’s over trillion dollars today and you might say “Wait a second. Wasn’t there a boom and a bust in these dotcoms? How come we don’t see that on this graph. That was a Wall Street phenomenon, not a main street phenomena. The actual adoption of these technologies for smooth exponential growth but the investment community looked at the internet in the late 1990s and said “Wow, this is going to change everything, this is going to turn every business model on its head, it’s all the values that these dotcoms swore.” And that was a correct perception and it was going to do so exponentially but that doesn’t mean instantaneously, if you remember my graph of the internet on the linear graph it was drawing exponentially but it look like nothing was happening for 10 years, then finally it exploded, so Wall Street came back three years later on 1999–2000, since he hasn’t changed everything. I guess we were wrong and all the values went the other way. In fact this boom-bust psychology is an accurate harbinger what ultimately ends up being a true revolution.

We saw it in telecommunications, we saw it in AI, in fact, we saw it in the rail roads in the nineteenth century and now the internet and the Ecommerce is a true phenomenon. You can argue whether Google is 37 to 1 price earnings ratio is high or low, but it’s not 10,000 to 1. They do have $12 billion of real revenue. This is now starting to be quite transformative and as we get broadband everywhere and as broadband goes to Ultra Broadband, this will become even more transformative and comprising even larger part of the economy. So, early in the next decade, computers will really begin to disappear, they’re already disappearing, may I have my whole photo collection and movie collection on a 4 Gigabyte flash drive which is the size of my fingernail and I have lost it. People complain that they lose their nano-iPods as I mentioned we’ll solve this problem that people like large displays on the one hand, but they also like devices even smaller than this, we’ll put them in eye glasses, they’ll beam images directly to our retinas, creating either virtual displays at a high definition floating in air or creating a full emergent virtual reality experience, so one of the applications which you are aware of at this conference, Telepresence, for things like surgery, doctors can actually feel like they’re with a patient and examine their symptoms from afar or virtual reality surgery, a surgeon that’s operating on the eye and this is an actual technology that’s utilized, can be in a operating theater with the eyes as this big and then they perform surgical functions on that virtual eye, it gets translated to very fine precision movements of robotic surgeon. This is used by the militarium like a on the Army Science Advisory Board and there’s a big movement to take the soldier out of the weapon, but make the soldiers feel like he or she in the weapon but through remote communication and put the soldier in a virtual reality environment and even if they’re in the weapon like an Abrams tank, , they’re not going to just open the window and look outside, they are in a virtual reality environment. This technology exists today, I’ve tried these systems.

Stanford has a very high quality system that you put on these goggles and it appears like you’re in another environment and it mentions how your head moves or you really feel like you’re inside that environment, interesting experiments where they put you in front of a cliff and then tell you to jump and even though people know that they’re in a room, that they won’t jump, it’s so realistic. This will be ubiquities technology, inexpensive, early in the next decade, this really will solve the problem that people like to watch movies on devices this big but they don’t really like an image that’s only one inch in size. So we are able to actually control our visual experience. You can go to a virtual visual auditory environment, design up new environments will be a new art form, so you can meet like we’re meeting now, and in fact I do this now with speeches but you can also have more intimate encounters, business meetings and so on that are in these virtual visual auditory environments. Perhaps a most important application will be augmented real reality. There’s already cars where the navigation system is not some little display on the side, whether it’s actually has animation right on the road by building it into the windshield, but this will be in our eyeglasses so as we look at someone, there’ll be a popup display reminding me this is birthday next Tuesday or reminding me of what people’s names are, that would be very helpful and we’ll have effective language translation providing subtitles on the word.

We’ll have interactions using natural language with virtual personalities to conduct routine transactions and this will be -- we’ll be online all the time with very high bandwidth, wireless connection, the electronics will be woven in our clothing, we’ll have the seamless mesh, it’s actually called the World Wide Mesh concept where each device is not just spoken at the internet, if you could consider your cellphone or your PC, these are not nodes on a network, they’re spokes into a network and then there’s a network but ultimately, all these devices with computing everywhere in the environment, internet clothing and everywhere we go will be nodes on this big network the World Wide Mesh. Now, there was not just sending and receiving your messages but also transmitting other messages, so every time you need to make a connection, it’ll self organize to provide that communication channel and also organize computation resources, so you need a million computers for half a second, it’ll just find those resources automatically, consider that right now, 99.9% of the computes on the internet are on youths. You’ve got all these computers that are sitting they’re doing nothing, somebody needs a million computers where the computation, can easily harness your computers, well, there are initiatives like the study at home and some medical simulations that are harnessing your computers if you’ve subscribed to them, but this will all be organized in a World Wide Mesh concept early in the next decade.

If you go out to 2029, it’s when these trends will really become mature, we’ll have a billion fold increase in the power of Information Technologies such as broadband by that time. We’ll have completed the reverse engineering of the human brain. It’ll be very powerful combination to take the pattern recognition powers of human intelligence with ways in which machines are already disappeared, they can remember billions of things accurately, they can transmit information at electronic speeds which are million times faster than human language. But most importantly, it’s not going to be an alien invasion of intelligent machines. It’s going to expand our physical and mental reach and very literally, it’s going to go inside our bodies and brains and expand our health and our ability to do cognitive functions. Nanobots which already and I mentioned these are first generation of these devices already being used in animals, we’ll be very sophisticated a quarter of a century from now. They’ll be going inside our bodies, keeping us healthy from inside, augmenting our immune system. They’ll go inside our brains, interact with our biological neurons, there’re already people with computers inside their brains, not get blood cell size but pea size. If you have Parkinson disease, you can have a computer put in your brain, that replaces the biological neurons destroyed by that disease and this is an FDA approved treatment and the biological neurons are signals from these healthy neurons and not getting signals from the computer, that works just fine. The latest generation of this FDA approved neuro limb plan actually allows you to download new software to the computer inside your brain from outside the patient. We’ve lots of devices inside the body and brain already that have two way communication, so it was pea size today, apply this 100,000 fold, decrease in size in billion fold increase in capability of the next quarter century and these would be blood cell size devices, millions of them, in our brains interacting with our biological neurons. So, you want to go in virtual reality, the nanobots shut down the signals coming from your real senses, replace them with the signals that your brain would be receiving if you were in the virtual environment and then you feel like you are in that virtual environment and again the design of these environments will be in new odd form, some will be recreation of earthly environments like a Mediterranean beach or the Tajmahal. Some of the fantastic imaginary environments that can’t exist on earth, you can go there by yourself or go there with other people and incorporate all of the senses. You would actually don’t have to be the same person, you can become a different person, you go to move your arm, it moves your virtual arm, design a virtual bodies to go with these virtual environments will be part of the same design of that environment, but most importantly, it’s going to expand human intelligence which arguably, our computers already do.

I mean every time you use a search engine, you’re plugging into a quite impressive manner, this exponentially growing human knowledge base where there were species that has knowledge altogether and we have increasingly intelligent ways of accessing it, these computers are getting closer to us, we can already search the internet, with devices that fit in your pocket, these ultimately will be in our bodies and brains, it’s actually pretty convenient place to put them and this will be an expansion, a continuation of this exponential expansion of the mental powers of our human machine civilization and I’ll leave you with one last trend before we take -- I’ve some dialogue about this. Human life expectancy is not being a constant. This is the part of the process of human is extending our reach. When our genes evolved thousands of years ago, it was not in the interest of the species for the people to live on average past childhood because then you are just using up the very precious and limited resources of the tribe, so human life expectancy was in the twenties, 2000 years ago. It was 37 in 1800, that’s only 200 years ago. There was no sanitation, so there were rampant bacterial infections, there were no antibiotics, human almost died in their thirties and that was typical. It was 48 in 1900. It’s now pushing 80, but as we get to the matured part of this ability to reprogram biology with biotechnology, with this, we’ll go into high gear, then according to my models, 15 years from now, we’ll be adding more than a year every year, not just an infant life expectancy, but to your remaining life expectancy. So that’s a tipping point, as we go forward a year, your remaining life expectancy will move on away from you, so if you can hang in there for another 15 years, we’ll get to experience the remarkable century ahead. Thank you very much.

Ray Kurzweil: Are there microphones? If not, I can probably hear you.

Speaker: Just wondering how long it’s going to take the nanotechnology, bio, electric for us to have brainpower?

Question 1: Just wondering how long it will take nano technology bioelectric for us to have this great power?

Ray Kurzweil: Actually none of us are all that smart by ourselves. We are all benefiting from in fact this interconnectedness that broadband provides and there is this concept “the wisdom of crowd”. So, when a crowed like this is very wise, if we can actually harness that brain power together, it is very interesting experiments on that where you take a crowd and if you use like embedding power, which was a good way of accessing that wisdom, markets are very good way of harnessing, there is no one personal is everything going on, but the whole crowed knows everything that’s going on the market. Beside of a market, mechanism they can actually estimate for example, the number of beans and the jar extremely accurately and better than any of the individuals and instead of these bedding parlours to predict the election, they were much better than the polls, they were accurate in 49 out of 50 states, it is actually very high degree of precision in the last election, so that’s actually one way in which we can use broadband and the power of network to amplify all of our intelligence.

Question 2: More on speaking of amplifying intelligence, I focus my research in work that I do Telepresence, I focus my research on Telepresence, because it is actually bringing people together all over the world and allowing, I think Thomas Friedman called it one of the great steroids, the acceleration of knowledge of research of learning, where do you stack that on the Telepresence on the importance of, some of the steroids and do you have any comments on Telepresence?

Ray Kurzweil: Telepresence is really on the cutting edge of this sharing of information. It is form of virtual reality and it is really a harventure of what’s to come. I think it is a tremendously powerful thing to be able to have a world renowned medical expert to be really present with you if the patient is may be in Africa or something. Education to really feel like you are with an educator and just the ability to meet with each other, human communication is one of things that makes us unique, but Telepresence is on the cutting edge of our being able to meet without being limited by geographical limitations and as broadband gets higher and higher quality all these other display technologies get higher and higher resolution to the reality of Telepresence in a virtual reality is getting more and more compelling. Ultimately you will all compete very well with real reality, so in the case in the universities that students not necessarily got a class they can watch it using video conferencing on the Internet archived, it is perhaps looks crude compared to real reality today, it is actually quite satisfactory, but ultimately it will be just as realistic as being there and the ability to really meet including all of the senses without the people using Telepresence, I think it is quite revolutionary, things like Second Life as a whole another virtual reality environment, now looks crude today, but think how crude video games were when they started pong with stimulation of tennis, but it is was pretty crude, these games have become quite realistic. Things like Second Life will be a whole virtual reality environment that’s ultimately be as competing with real reality with many advantages…

Question 3: Have you considered what’s sort of social constrains of rules might have to go along with the kind of virtual reality that you talked about, where you would actually be shutting down your sensory receptions substituting in other, because if that was done to you against your will and some one substitute are very unpleasant reality that will be…

Ray Kurzweil: We have early harventures of these issues now and that we do very intimate in things on our computers, with people do go in just to chat room, is a form of virtual reality, you are in another environment people take on a persona in personality, people can misrepresent themselves, all these technologies can be used for creative or destructive purposes. We do need to establish new paradigms and also be able to verify who people are, maintain our privacy, so there is this ongoing race between encryption and decryption. Actually, cell phones today are pretty good encryption better than the old cell phones, I would say we are doing OK despite the rampants identity theft and so on, but these are issues with today’s technology and there is when we do have computers running inside our bodies and brains and some people do have them and those computer do communicate. Thinks I saw for viruses, spyware, software that might actually influence the software running inside your body and brain becomes even that much more important.

Computers already extension of ourselves, this one even set her 10-year-old computer may as well be inside his brain, because he carries it everywhere he goes, when she comes in the doorway, she uses another window because she has got five or six windows open on his screen and so these computers are already extensions of ourselves, we can already see these issues. My own feeling is we are benefiting more than we are harmed, but the downside of these technologies is something that concerns me. I have been actually very active up on fairly serious downside, which is abusive biological technologies, same technology they could enable us to over come cancer by reprogramming biology, it could also abused by a bio-terrorist to reprogram a biological virus to be more deadly and more stealthy and more communicable and the good news is we actually have the technologies to protect ourselves, RNA interference can turn off viruses, viruses or genes and I have described rapid response system that we need to put in place that if a new biological viruses destructive emergence, where it is natural like it can evolve bird flu or unnatural like a terrorist weapon, we could respond very quickly with a solution to that in the matter of days. It took us five years to sequence HIV, we sequence SARS in 31 days. We can now sequence a virus in one or two days, we could in a week have a rapid response to a new biological virus.

One area where we do this well is software viruses, where there is a new Software virus we capture, reverse engineered create an antidote, spread the antidote widely out in the Internet and it actually works pretty well not perfect, we can’t cross Software virus so far concern list, but nobody has taken down even a portion of the Internet for even one second of the last 10 years. Well, we need to do something similar in biological technologies, but all these technologies are double end swords.

Question 4: Hi, just our little concern that you have talked about neuron, you are talking about neurons doing everything, until last six years we have known that the neurons are all controlled by glea’s and they grow where the gleas want them to, they fire when the gleas tell them to, every glea is connected, no neuron is connected, we really have a glea brain, not a neuro brain and …

Ray Kurzweil: It is true, we have more gleal cells and that is going to be part of reverse engineering of the human brain, but these – in fact there are some good models and simulations of gleal cells. Ultimately, that will be part of the reverse engineering of the human brain. We do find that for certain regions of the brain we don’t necessarily have to simulate them at the cellular level, we can simulate what the whole region does in transforming information and these simulations are in different levels. IBM simulation of cerebral cortex is right now at the cellular level including neurons and gleal cells and ultimately we will be at the molecular level. Some of these other simulations are actually simulating what the whole region does, but you make a good point that gleal cells are definitely an important part of the brain.

Question 5: The electric infrastructure in silicon valley is really straining under the increase requirements of the computation explosion that has happened there as we moved to the 20-30 time frame and then the big increase in computation, what limitations is that have for our energy consumption and the ability of the society to create that level of energy?

Ray Kurzweil: OK, I said that I would talk about energy and we actually are a wash in energy, we have plenty of energy in our myths, but we are not capturing it, if we captured one part in 10,000 of the sunlight that falls on the earth, we would meet 100% of our energy needs. Now, we don’t do that today, we could sell a panels on not information technology they are all in industrial technology they are very heavy, cumbersome, and inefficient, expensive, hard to install. There is a new generation of nano engineered cell of panels with some actually multi hundred million dollar venture of funding that’s promised to make the next generation of nano engineered cell of panels competitive with fossil fields, but if you go out 20 years, we have full scale electrical nano assembling, you can create these very inexpensive, but powerful macro objects by reassembling that on energy at the molecular level, using information massively powered information processes to be able to create extremely inexpensive cellular panels and it is very low cost capture where it will then be three parts in 10,000, with cell of very tiny fraction of the sunlight. It is been shown that even a current efficiency is we do only have to put solo panels on less than 1% of the lands in United States, 30% is completely unused with things like desert, deserts are actually very good for solo panels, we need to store the energy because of the intermediacy of the sun, but nano engineered field cells will be hardly decentralized solutions for that. There are dozen of other scenarios for being able to meet our energy needs, even greatly expanded energy needs with these nano technology and this is certainly not discussed in when people talk about global warming, it is of these current trends are going to go on for hundreds of years, completely ignoring these emerging technology, look at another way right now, solar energy needs one part in a thousand of our energy needs. Well, one part in a thousand that seems pretty trivial, it’s easy to dismiss, it’s doubling every two years and has been will continue to do that based on if you look at the business plans of these various companies doubling every two years, is multiplied by a thousand in 20 years. I believe within 20 years we will be replacing fossil fields with there information based nano technology solutions.

Question 6: Your predictions of the future are actually pretty optimistic I think in terms of things will workout, I am curious – would you comment on obviously sensing silicon or sensing computers and will we actually have nano technology that improves humans to keep up with computers or all some point carbon base life forms become obsolete?

Ray Kurzweil: Well, it depends on how you define human, I do believe we are going to transcend our biology, we are starting to do that. We are going to be adding non-biological systems to out carbon based biological systems and there are people who have already done that and in fact all of us who are putting it pretty close to our bodies have augmented capabilities with our technology. One thing you should take note of is that, the biological capabilities we have 10 of the 26 file calculation for second among all human beings. 50 years from now, that’s going to be 10 of the 26 powers, biological intelligence is fixed. The non-biological intelligence is growing exponentially, it is we are adding three zeros every decade and even that’s going to continue, so it is going to actually show passed in the 2020 if you get to the 2030’s and 2040’s we are going to be much more of a non-biological civilization than a biological one. It is still in my mind human intelligence, this is the human technology civilization, but ultimately that technological portion is growing, you could say biological evolution is continuing, but it’s at a speed that’s thousands of times slower than technological evolution. We ultimately will be more non-biological than biological. Now, here that they go “I don’t want to become mostly a machine”, because they are thinking of machines, like this machine which is still millions of times simpler than the human being, it doesn’t have that suttle and supple e saddle qualities of human intelligence, that’s really the nature of my prediction, the nature of a machine is going on to go the transformation is going to be quite different. So, in my mind we are going to ultimately transcend our biology to subtitle in my life’s book is “When Human Transcend Biology”, but we are not going to transcend our humanness we are still going to be human, the silly human civilization even if we have a large portion of our intelligence in non-biological form.

Question 7: Great I just want to point out, over the past 4.5 billion years we have evolved to this stage and then it still was accelerated over the last 7 million years, although in the last 30,000 years or so, we have kind of slowed down our evolution, instead we have an epigenetic evolution which basically is what you have been talking about on a cultural basis. Now, given that emergence, you have noted that in 2029 by then you predict we will have the reverse engineering of neural circuitry, at what point do you think there may be the igniting or the emergence of something like Gaya?

Ray Kurzweil: Well, first of all biological evolution hasn’t stopped and even among human beings is actually been genetic changes in the last thousand years which is interesting side note, your point is well taken. Technological evolution is thousands and ultimately it will be millions of times faster than biological evolution, if Gaya you mean some kind of universal consciousness. If you take all human beings today and we tie together with all these broadband and networking applications there is an intelligence represented by all of that connected intelligence. So, it’s a philosophical issues that how you regard that, but it does have a personality and it is able to actually to find out information on all these blogs interacting with each other. Each blog may be unreliable, but the whole system actually can find out the truth involves in circumstances pretty accurately. I think it is basically very democratizing force, although, it certainly can’t be abused. In my first book in the 1980’s “The Age of Intelligent Machines”, that the Soviet Union which was then going strong was doomed because of these emerging decentralized electronic communication, e-mail using these teletype machines and the fax machines where much more powerful than the copiers they had been banning and that ultimately this would destroy the Tele tank control and I think that’s what we saw in the coup against Gorbachev in 1991. It wasn’t Yeltsin standing on a tank, that was Fatwa that over turned that code, it was a clandestine network of decentralized electronic communication. It had a big movement towards democracies in the 1990’s, I mean these notable hold-outs and you can read about them everyday in paper, but they are actually fairly few now. If you go back a few decades where they were very few democracies and we had democratization other levels with society. If you have a chronic disease and you go to see your doctor, you are probably in touch with the people who have that disease around the world and you keep in touch with latest research and you go into your doctor armed with that information, so it changes the nature of the relationship. So, there is a raising of consciousness through sharing of information and knowledge.

Question 8: Yes, one of the greatest advances for our civilization is this spreading of education and one of our challenges today is the disparity between the qualities of education with some folks receive versus other folks. They have been experiments and trying to use technology to improve education, but research that I have seen, indicates that it hasn’t really worked, it really need that human interaction and I am just curious, if you have any insights or thoughts on why the technology having people use computers, do take tests and so on and computers respond and give them different questions, has that really been that effective in raising the quality of education and if may be technology does in the future have some solutions for raising the quality of education across the board?

Ray Kurzweil: Well, it depends what you mean by education? It include the whole learning experience of children that deeply influenced by computers, networks and learned tremendous amount, I see my own kids who have now had access to search engines and all these knowledge out in the web and it has definitely transformed their access to knowledge and the knowledge that they have been able to absorb. And things like Telepresence and the whole virtual reality that’s emerging is going to be very powerful, I am on the visiting committee of the MIT Media Lab and we have this one laptop per child project and these are other competing projects, but they hope to actually provide every kid in Africa with a very powerful system device that is broadband enabled, will be able to communicate, create all these communities with all the kids in Africa and around the world with these ill devices they can create a motion picture, recorded albums, software these can be very powerful devices and do Telepresence with educators office, an educator in their language, somewhere they cannot communicate with that person and it is going to able really accelerate in educational process. There are lot of kids learning to read using computers, I mean I think there is certain instructions does work in various areas. One of my committees has a product for dyslexia kids that helps teaching to read and to be able to read and tales, they go through the day. It has been deeply influential, unfortunately our schools very often are lagging adopters of technology, we don’t provide them the funding. So, they get the handy down, there are still emerging schools with Apple tools, so it is a matter of priority. We do find other areas of the world like for example, India and China are now – well take China, produce 10,000 engineers per year, 20 years ago to 60,000, we are now at about 53,000 and they have gone from 10,000 up to 300,000 a year and so they are training more of their citizens to be scientifically literate. So, there are issues there, but I think technology has been transformative.

Moderator: One more question here it is.

Question 9: A sort of more near term question that close to lot of us in the room, which is some also made multi million dollar bet, some also thinking about making multi million dollar bets on, do you need this fiber optics stuff to your home and all this bandwidth going to be needed or do we all just wait until wireless comes around and we don’t need any fiber in area or two in the actual specific home. So, you can tell us, which technology probably to bet on, but it is do we need this much bandwidth like we all believe we need or…

Ray Kurzweil: Well, first of all I give one part of my response as a same advice I give to people that come confused at what cell phone they should buy or what computer they, because are concern they are going to buy something and this going to be obsolete and if you wait for things to settle down, you will be waiting forever and very important issue is to really research and adopt and consider these trends which are quite predictable as to regarding the exponential growth of communication computer technology. We bake these into our plans, every six months part of our plan is a description of what will be feasible in terms of all the enabling technologies, portable devices and broadband communications, we have all description of the technology world at each point in time and build our plan accordingly. It is very important to do that and it is really surprising how many sophisticated companies don’t do that and don’t really have a realistic notion of what will be feasible at different points in time. So, if you have a five year plan, the world is going to change a lot in all these dimensions and truly understand where we will be, but as far the basic question, are we going to need more bandwidth? The answer is absolutely yes. There is tremendous of benefits to virtual reality, Telepresence type systems where you can be with someone else, as if you are together and create these communities based on common need, whether it is education or sharing your business information or social encounters, not be limited by geography. Ultimately it is going to require to really be as if you are in together with someone in a virtual environment it is going try tremendous bandwidth, but tremendous bandwidth is coming and these applications are literally waiting for the enabling technologies to make them feasible.

Thank you very much.